Title: A novel genetic algorithm for the maximum coverage problem in the three-level supply chain network

Authors: Omid Rahmani; Bahman Naderi; Mohammad Mohammadi; Mehrdad Nouri Koupaei

Addresses: Department of Industrial Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran ' Department of Industrial Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran ' Department of Industrial Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran ' Department of Industrial Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran

Abstract: The maximum coverage problem is one of the most functional location issues. Nowadays, organisations are seeking to increase profits and one of the competitive advantages for organisations is efficient and effective designing of supply chain network. On the other hand, given the importance of distribution planning among the levels of supply chain, vehicle routing problem needs to be explored which leads to a significant reduction in costs of supply chain network. The purpose of this research is designing a supply chain network that includes the supply, distribution centres and retailers. It should be noted that the coverage radius is defined for all distribution centres and distribution centres gives any services to retailers that is within the actual coverage. Also, this service is done on routing. Since that the classical vehicle routing problem is NP-hard, to solve the problem in small and medium sizes, we used the GAMS software. Next, genetic algorithms and simulated annealing is used to solve the problem in large size. Finally, the results have been evaluated.

Keywords: the maximum coverage problem; three-level supply chain network; genetic algorithm; simulated annealing.

DOI: 10.1504/IJISE.2018.094844

International Journal of Industrial and Systems Engineering, 2018 Vol.30 No.2, pp.219 - 236

Received: 19 Apr 2016
Accepted: 28 Oct 2016
Published online: 25 Sep 2018 *

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